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Understanding Data Science and Data Analysis Life Cycle

Pickl AI

Overview of Typical Tasks and Responsibilities in Data Science As a Data Scientist, your daily tasks and responsibilities will encompass many activities. You will collect and clean data from multiple sources, ensuring it is suitable for analysis. This step ensures that all relevant data is available in one place.

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Artificial Intelligence Using Python: A Comprehensive Guide

Pickl AI

Data Preparation for AI Projects Data preparation is critical in any AI project, laying the foundation for accurate and reliable model outcomes. This section explores the essential steps in preparing data for AI applications, emphasising data quality’s active role in achieving successful AI models.

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Predicting Heart Failure Survival with Machine Learning Models — Part II

Towards AI

That post was dedicated to an exploratory data analysis while this post is geared towards building prediction models. Feel free to try other algorithms such as Random Forests, Decision Trees, Neural Networks, etc., Data Preparation Photo by Bonnie Kittle […] among unsupervised models.

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Large Language Models: A Complete Guide

Heartbeat

In this article, we will explore the essential steps involved in training LLMs, including data preparation, model selection, hyperparameter tuning, and fine-tuning. We will also discuss best practices for training LLMs, such as using transfer learning, data augmentation, and ensembling methods.